Solar energy is used in many applications, such as increasing water’s temperature or moving electrons in a photovoltaic cell, agriculture planning, fuel production, electricity production, transport, architecture and urban planning, etc. Solar energy is secure, clean, and available on the Earth throughout the year. Its secure and clean applications are very important to the world, especially at a time of fossil fuel high costs and the critical situation of the atmosphere resulting from fossil fuel applications. Solar techniques include the use of photovoltaic systems, concentrated solar power and solar water heating to harness the energy. In this paper, prediction is focusing in the Southern part of India and the solar light will be available from 8 to 9 months in a year in this region. So to utilize the solar energy in an efficient way the prediction is done. To predict the availability of solar energy the machine learning Temporal Gaussian Process Regression(TGPR) method has been used. It provides better result and also more robust when compared with the methods like ELM, SVM, etc. The predicted values are used to measure and analyze the amount of energy that could be generated during a year in the southern region of India. This in turn can be utilized to identify the suitable solar based devices suitable for different locations.